1 / 33

Randomized Algorithms CS648

Randomized Algorithms CS648. Lecture 13 Expected duration of a randomized experiment Part I. coupon Collector Problem. Coupon Collector Problem. There is a bag containing distinct coupons. Each coupon has a unique label from [ ]. Experiment: Repeat

trevor
Télécharger la présentation

Randomized Algorithms CS648

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Randomized AlgorithmsCS648 Lecture 13 Expected duration of a randomized experiment Part I

  2. coupon Collector Problem

  3. Coupon Collector Problem • There is a bag containing distinct coupons. • Each coupon has a unique label from []. Experiment: Repeat 1. Select a coupon randomly uniformly from the bag 2. Note down its label 3. Place the coupon back into the bag Until every coupon has appeared at least once : the number of iterations of the loop (number of coupons drawn). Question: What is E[] ?

  4. Example =5 1 4 5 2 3 5 3 5 2 2 1 2 3 1 3 3 2 1 5 4 1 4 5 1 1 3 2 5 3 3 2 3 1 3 3 1 2 2 1 5 1 3 5 3 4 Done in 14 samplings Done in 12 samplings 2 5

  5. Coupon Collector Problem : the number of iterations of the loop (number of coupons drawn). Question: What is E[] ? Standard method: E[] = ? No easy way !!

  6. Coupon Collector Problem no coupon seen all coupons seen This transition is not sudden. In fact it is a gradual transition through various discrete stages. Can you see these discrete stages ?

  7. Coupon Collector Problem no coupon seen all coupons seen 1 2 3 4 This transition is not sudden. In fact it is a gradual transition through various discrete stages. Can you see these discrete stages ?

  8. Reviewing Example =5 1 4 5 2 3 5 0 3 1 3 3 1 2 2 1 5 1 3 5 3 4

  9. Reviewing Example Each instance of coupon collector problem has to pass through these stages. Does it give you some inspiration to calculate E[X] ? =5 1 4 5 2 3 1 0 1 3 3 0 5 4 2 3 5 2 4 2 1 4 0 5 3 2 5 2 1 2 3 3 1 3 2 5 1 4 1 5 4 1 1 3 2 5 3 3 2 3 1 3 3 1 2 2 1 5 1 3 5 3 4 2 5

  10. Coupon Collector Problem : the number of iterations of the loop (number of coupons drawn). Question: What is E[] ? no. of coupons sampled from the moment ?? to the moment ?? th distinct coupon was selected th distinct coupon was selected

  11. Reviewing Example =5 1 4 5 2 3 1 0 5 4 3 2 =1 =1 =4 =3 =5 3 1 3 3 1 2 2 1 5 1 3 5 3 4 This picture validates the equality

  12. Coupon Collector Problem : the number of iterations of the loop (number of coupons drawn).  Question: What is ] ?

  13. Calculating E[] Experiment (in th stage): Repeat 1. Select a coupon randomly uniformly from the bag 2. Note down its label 3. Place the coupon back into the bag Untilth distinct coupon appears.

  14. Calculating E[] Experiment (in th stage): Repeat 1. Select a coupon randomly uniformly from the bag 2. Note down its label 3. Place the coupon back into the bag Untilth distinct coupon appears. =Probability an iteration is successful Question: What is ? E[] = = = =

  15. Coupon Collector Problem : the number of iterations of the loop (number of coupons drawn).  Theorem: Expected duration of coupon collector experiment is .

  16. Discrete Random Walk on a LINE

  17. Discrete Random Walk • Particle starts from origin • In each second, particle moves 1 unit to the left or to the right with equal probability. • While at origin, the particle moves to 1 always. Question: What is the expected number of steps of the random walk to reach milestone n? 0 1 2 3 4 5 6 7 8 … n n+1

  18. An example 0 1 2 3 4 5 6 7 8 … I,and perhaps you too, could not notice the walk. So let us trace the walk slowly.

  19. Formalism : No. of steps of a random walk which starts at and terminates on reaching for the first time. Aim: To calculate E[]

  20. Careful look at the example 0 1 2 3 4 5 6 7 8 … Can you break the walk08into stages ? Think carefully …

  21. Careful look at the example 0 1 2 3 4 5 6 7 8 … Walk starting from 0 and terminating at 5

  22. Careful look at the example 0 1 2 3 4 5 6 7 8 … Walk starting from 0 and terminating at 5 Walk starting from 5 and terminating at 8

  23. Relation among ’s For any = + Breaking down to the limits, we get = Hence using linearity of expectation E[] = ]

  24. Relation among ’s 0 1 2 3 4 5 6 7 8 … 1 1 3 1 5 1 5 11

  25. How to calculate E[] ?

  26. Conditional Expectation Given any event and a random variable defined over a probability space (,P). E[] = E[| ] P() + E[| ] P() E[| ] E[| ] Ω A useful tool to calculate expected value of a random variable

  27. Calculating E[] E[] = ?? = ½ E[| first move is L] + ½ . 1 = ½ E[| first move is L] + ½ 0 1 … +1 ½ E[| first move is L] + ½ E[| first move is R] ?

  28. Calculating E[| first move is L] E[| first move is L] = ?? = 1 + E[]+ E[]//by linearity of expectation 0 1 … +1 1 + E[]

  29. Calculating E[] E[] = ½ E[| first move is L] + ½ . 1 = ½ + ½ . 1 = 1 + ½ 2 E[] = 2 + ]  E[] = 2 + Question: What is E[] ? Question: What is E[] ? Question: What is E[] ? Answer: ?? 0 1 … +1 3

  30. Calculating E[]

  31. Calculating E[] Lemma (just proved): E[] = E[] = = = = = 0 1 2 3 4 5 6 7 … +1

  32. Theorem:Expected number of steps of a random walk starting from 0 and terminating on reaching is .

  33. Expected duration of a random experiment Let Xdenote the random variable for the duration of a randomized experiment. To calculate E[X], the following approach is sometimes useful: • Partitionthe experiment into stagescarefully. • Calculate expected duration of each stage. • Using linearity of expectation, calculate E[X]. In the next class, we shall discuss more non-trivial randomized algorithms which are analyzed using this method.

More Related